$df_selected_vars
order var_name var_number var_letter var_role doble_reference
1 1 mpg 1 A VR VR(mpg)
2 2 cyl 2 B X X(cyl)Simple Linear Regresion - Fixed Model - General Linear Models
Report - Anova 1 Way - Fixed Model - General Linear Models
1) References
2) Linear Regresion - Table
$df_table_reg
Estimate Std. Error t value Pr(>|t|)
(Intercept) 37.88458 2.0738436 18.267808 8.369155e-18
X -2.87579 0.3224089 -8.919699 6.112687e-103) R^2 and Ajusted R^2
$df_table_det_coef
r.squared adj.r.squared f.obs df_num df_den p.value
0.72618 0.7170527 79.56103 1 30 14) Position
$df_position
rol_var var_name n min mean median max
1 VR mpg 32 10.400000 2.009062e+01 19.2000000 33.900000
2 X cyl 32 4.000000 6.187500e+00 6.0000000 8.000000
3 residuals --- 32 -4.981416 -2.111755e-16 0.2217446 7.5185845) Dispersion
$df_dispersion
rol_var var_name n range variance sd
1 VR mpg 32 23.5 36.324103 6.026948
2 X cyl 32 4.0 3.189516 1.785922
3 residuals --- 32 12.5 9.946266 3.1537701) Requeriment - Normaility test - Residuals
$test_residuals_normality
Shapiro-Wilk normality test
data: minibase_mod$residuals
W = 0.96323, p-value = 0.33592) Requeriment - Homogeneity visual evaluation - Residuals
$df_table_plot001
rol_var var_name n min mean median max
1 VR mpg 32 10.400000 2.009062e+01 19.2000000 33.900000
2 X cyl 32 4.000000 6.187500e+00 6.0000000 8.000000
3 residuals --- 32 -4.981416 -2.111755e-16 0.2217446 7.518584$df_table_plot002
rol_var var_name n min mean median max
1 VR mpg 32 10.400000 2.009062e+01 19.2000000 33.900000
2 X cyl 32 4.000000 6.187500e+00 6.0000000 8.000000
3 residuals --- 32 -4.981416 -2.111755e-16 0.2217446 7.518584